{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "51eb43f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[93mExcluded notebooks:\u001b[0m\n",
      "  - 00_execute_all_notebooks.ipynb\n",
      "  - 00_check_urls.ipynb\n",
      "  - py54-forecasting-con-deep-learning.ipynb\n",
      "  - py54-forecasting-with-deep-learning.ipynb\n",
      "  - py61-m5-forecasting-competition.ipynb\n",
      "  - py65-accelerate-forecasting-models-gpu.ipynb\n",
      "  - py65-acelerar-modelos-forecasting-gpu.ipynb\n",
      "\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[1/58] Executing: \u001b[93mpy27-forecasting-series-temporales-python-scikitlearn.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py27-forecasting-series-temporales-python-scikitlearn.ipynb (Time: 45.56 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[2/58] Executing: \u001b[93mpy27-time-series-forecasting-python-scikitlearn-cn.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py27-time-series-forecasting-python-scikitlearn-cn.ipynb (Time: 43.16 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[3/58] Executing: \u001b[93mpy27-time-series-forecasting-python-scikitlearn.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py27-time-series-forecasting-python-scikitlearn.ipynb (Time: 41.75 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[4/58] Executing: \u001b[93mpy29-forecasting-demanda-energia-electrica-python.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py29-forecasting-demanda-energia-electrica-python.ipynb (Time: 189.86 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[5/58] Executing: \u001b[93mpy29-forecasting-electricity-power-demand-python-cn.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py29-forecasting-electricity-power-demand-python-cn.ipynb (Time: 196.54 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[6/58] Executing: \u001b[93mpy29-forecasting-electricity-power-demand-python.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py29-forecasting-electricity-power-demand-python.ipynb (Time: 195.04 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[7/58] Executing: \u001b[93mpy37-forecasting-visitas-web-machine-learning.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py37-forecasting-visitas-web-machine-learning.ipynb (Time: 12.20 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[8/58] Executing: \u001b[93mpy37-forecasting-web-traffic-machine-learning.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py37-forecasting-web-traffic-machine-learning.ipynb (Time: 11.90 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[9/58] Executing: \u001b[93mpy39-forecasting-series-temporales-con-skforecast-xgboost-lightgbm-catboost.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py39-forecasting-series-temporales-con-skforecast-xgboost-lightgbm-catboost.ipynb (Time: 382.57 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[10/58] Executing: \u001b[93mpy39-forecasting-time-series-with-skforecast-xgboost-lightgbm-catboost-cn.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "\n",
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      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning:\n",
      "\n",
      "Glyph 27010 (\\N{CJK UNIFIED IDEOGRAPH-6982}) missing from font(s) Arial.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning:\n",
      "\n",
      "Glyph 35201 (\\N{CJK UNIFIED IDEOGRAPH-8981}) missing from font(s) Arial.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning:\n",
      "\n",
      "Glyph 22270 (\\N{CJK UNIFIED IDEOGRAPH-56FE}) missing from font(s) Arial.\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py39-forecasting-time-series-with-skforecast-xgboost-lightgbm-catboost-cn.ipynb (Time: 366.25 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[11/58] Executing: \u001b[93mpy39-forecasting-time-series-with-skforecast-xgboost-lightgbm-catboost.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py39-forecasting-time-series-with-skforecast-xgboost-lightgbm-catboost.ipynb (Time: 369.07 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[12/58] Executing: \u001b[93mpy41-forecasting-criptomoneda-bitcoin-machine-learning-python.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py41-forecasting-criptomoneda-bitcoin-machine-learning-python.ipynb (Time: 40.97 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[13/58] Executing: \u001b[93mpy41-forecasting-cryptocurrency-bitcoin-machine-learning-python.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py41-forecasting-cryptocurrency-bitcoin-machine-learning-python.ipynb (Time: 35.10 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[14/58] Executing: \u001b[93mpy42-forecasting-probabilistico.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py42-forecasting-probabilistico.ipynb (Time: 350.92 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[15/58] Executing: \u001b[93mpy42-probabilistic-forecasting.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py42-probabilistic-forecasting.ipynb (Time: 350.94 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[16/58] Executing: \u001b[93mpy44-multi-series-forecasting-skforecast-español.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py44-multi-series-forecasting-skforecast-español.ipynb (Time: 329.61 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[17/58] Executing: \u001b[93mpy44-multi-series-forecasting-skforecast.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py44-multi-series-forecasting-skforecast.ipynb (Time: 327.80 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[18/58] Executing: \u001b[93mpy45-weighted-time-series-forecasting-es.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py45-weighted-time-series-forecasting-es.ipynb (Time: 6.78 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[19/58] Executing: \u001b[93mpy45-weighted-time-series-forecasting.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py45-weighted-time-series-forecasting.ipynb (Time: 6.47 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[20/58] Executing: \u001b[93mpy46-forecasting-series-temporales-incompletas.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Joaquin\\AppData\\Local\\Temp\\ipykernel_18548\\180034607.py:9: UserWarning: This axis already has a converter set and is updating to a potentially incompatible converter\n",
      "  ax.plot(\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py46-forecasting-series-temporales-incompletas.ipynb (Time: 9.87 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[21/58] Executing: \u001b[93mpy46-forecasting-time-series-missing-values.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Joaquin\\AppData\\Local\\Temp\\ipykernel_24772\\242201202.py:9: UserWarning: This axis already has a converter set and is updating to a potentially incompatible converter\n",
      "  ax.plot(\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py46-forecasting-time-series-missing-values.ipynb (Time: 9.96 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[22/58] Executing: \u001b[93mpy48-forecasting-demanda-intermitente.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py48-forecasting-demanda-intermitente.ipynb (Time: 174.02 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[23/58] Executing: \u001b[93mpy48-intermittent-demand-forecasting.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py48-intermittent-demand-forecasting.ipynb (Time: 168.75 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[24/58] Executing: \u001b[93mpy49-modelar-tendencia-en-series-temporales-modelos-de-arboles.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py49-modelar-tendencia-en-series-temporales-modelos-de-arboles.ipynb (Time: 20.11 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[25/58] Executing: \u001b[93mpy49-modelling-time-series-trend-with-tree-based-models.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py49-modelling-time-series-trend-with-tree-based-models.ipynb (Time: 20.75 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[26/58] Executing: \u001b[93mpy51-arima-sarimax-models-python-cn.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py51-arima-sarimax-models-python-cn.ipynb (Time: 46.61 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[27/58] Executing: \u001b[93mpy51-arima-sarimax-models-python.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py51-arima-sarimax-models-python.ipynb (Time: 47.26 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[28/58] Executing: \u001b[93mpy51-modelos-arima-sarimax-python.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py51-modelos-arima-sarimax-python.ipynb (Time: 46.55 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[29/58] Executing: \u001b[93mpy52-stacking-ensemble-modelos-forecasting.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py52-stacking-ensemble-modelos-forecasting.ipynb (Time: 82.00 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[30/58] Executing: \u001b[93mpy52-stacking-ensemble-models-forecasting.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py52-stacking-ensemble-models-forecasting.ipynb (Time: 82.15 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[31/58] Executing: \u001b[93mpy53-global-forecasting-models.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Feature Extraction:   0%|          | 0/20 [00:00<?, ?it/s]\n",
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      "Feature Extraction:  85%|████████▌ | 17/20 [00:49<00:10,  3.54s/it]\n",
      "Feature Extraction:  95%|█████████▌| 19/20 [00:49<00:02,  2.01s/it]\n",
      "Feature Extraction: 100%|██████████| 20/20 [00:49<00:00,  1.55s/it]\n",
      "Feature Extraction: 100%|██████████| 20/20 [00:49<00:00,  2.47s/it]\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\threadpoolctl.py:1226: RuntimeWarning: \n",
      "Found Intel OpenMP ('libiomp') and LLVM OpenMP ('libomp') loaded at\n",
      "the same time. Both libraries are known to be incompatible and this\n",
      "can cause random crashes or deadlocks on Linux when loaded in the\n",
      "same Python program.\n",
      "Using threadpoolctl may cause crashes or deadlocks. For more\n",
      "information and possible workarounds, please see\n",
      "    https://github.com/joblib/threadpoolctl/blob/master/multiple_openmp.md\n",
      "\n",
      "  warnings.warn(msg, RuntimeWarning)\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py53-global-forecasting-models.ipynb (Time: 765.07 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[32/58] Executing: \u001b[93mpy53-modelos-forecasting-globales.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Feature Extraction:   0%|          | 0/20 [00:00<?, ?it/s]\n",
      "Feature Extraction:   5%|▌         | 1/20 [00:11<03:37, 11.43s/it]\n",
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      "Feature Extraction:  20%|██        | 4/20 [00:11<00:29,  1.83s/it]\n",
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      "Feature Extraction:  65%|██████▌   | 13/20 [00:38<00:23,  3.42s/it]\n",
      "Feature Extraction:  75%|███████▌  | 15/20 [00:38<00:10,  2.13s/it]\n",
      "Feature Extraction:  85%|████████▌ | 17/20 [00:47<00:08,  2.99s/it]\n",
      "Feature Extraction:  95%|█████████▌| 19/20 [00:48<00:02,  2.02s/it]\n",
      "Feature Extraction: 100%|██████████| 20/20 [00:48<00:00,  1.72s/it]\n",
      "Feature Extraction: 100%|██████████| 20/20 [00:48<00:00,  2.44s/it]\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\threadpoolctl.py:1226: RuntimeWarning: \n",
      "Found Intel OpenMP ('libiomp') and LLVM OpenMP ('libomp') loaded at\n",
      "the same time. Both libraries are known to be incompatible and this\n",
      "can cause random crashes or deadlocks on Linux when loaded in the\n",
      "same Python program.\n",
      "Using threadpoolctl may cause crashes or deadlocks. For more\n",
      "information and possible workarounds, please see\n",
      "    https://github.com/joblib/threadpoolctl/blob/master/multiple_openmp.md\n",
      "\n",
      "  warnings.warn(msg, RuntimeWarning)\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py53-modelos-forecasting-globales.ipynb (Time: 858.02 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[33/58] Executing: \u001b[93mpy56-forecasting-series-temporales-con-xgboost.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py56-forecasting-series-temporales-con-xgboost.ipynb (Time: 289.37 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[34/58] Executing: \u001b[93mpy56-forecasting-time-series-with-xgboost.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py56-forecasting-time-series-with-xgboost.ipynb (Time: 276.84 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[35/58] Executing: \u001b[93mpy57-interpretable-forecasting-models.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py57-interpretable-forecasting-models.ipynb (Time: 17.19 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[36/58] Executing: \u001b[93mpy57-modelos-forecasting-interpretables.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py57-modelos-forecasting-interpretables.ipynb (Time: 18.61 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[37/58] Executing: \u001b[93mpy58-forecasting-series-temporales-con-lightgbm.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py58-forecasting-series-temporales-con-lightgbm.ipynb (Time: 122.64 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[38/58] Executing: \u001b[93mpy58-forecasting-time-series-with-lightgbm.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py58-forecasting-time-series-with-lightgbm.ipynb (Time: 120.86 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[39/58] Executing: \u001b[93mpy59-modelos-forecasting-escalables.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py59-modelos-forecasting-escalables.ipynb (Time: 421.23 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[40/58] Executing: \u001b[93mpy59-scalable-forecasting-models.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py59-scalable-forecasting-models.ipynb (Time: 418.67 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[41/58] Executing: \u001b[93mpy60-forecasting-probabilistico-intervalos-prediccion-forecasting-multi-step.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py60-forecasting-probabilistico-intervalos-prediccion-forecasting-multi-step.ipynb (Time: 75.38 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[42/58] Executing: \u001b[93mpy60-probabilistic-forecasting-prediction-intervals-multi-step-forecasting.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py60-probabilistic-forecasting-prediction-intervals-multi-step-forecasting.ipynb (Time: 75.14 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[43/58] Executing: \u001b[93mpy62-deteccion-anomalias-series-temporales.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py62-deteccion-anomalias-series-temporales.ipynb (Time: 48.68 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[44/58] Executing: \u001b[93mpy62-time-series-anomaly-detection.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py62-time-series-anomaly-detection.ipynb (Time: 47.10 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[45/58] Executing: \u001b[93mpy63-data-leakage-modelos-forecasting-preentrenados.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py63-data-leakage-modelos-forecasting-preentrenados.ipynb (Time: 5.59 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[46/58] Executing: \u001b[93mpy63-data-leakage-pre-trained-forecasting-models.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py63-data-leakage-pre-trained-forecasting-models.ipynb (Time: 5.29 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[47/58] Executing: \u001b[93mpy64-clustering-series-temporales-forecasting.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Feature Extraction:   0%|          | 0/20 [00:00<?, ?it/s]\n",
      "Feature Extraction:   5%|▌         | 1/20 [00:12<04:05, 12.91s/it]\n",
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      "Feature Extraction:  80%|████████  | 16/20 [00:41<00:06,  1.68s/it]\n",
      "Feature Extraction:  85%|████████▌ | 17/20 [00:49<00:09,  3.28s/it]\n",
      "Feature Extraction:  95%|█████████▌| 19/20 [00:49<00:01,  1.98s/it]\n",
      "Feature Extraction: 100%|██████████| 20/20 [00:50<00:00,  1.63s/it]\n",
      "Feature Extraction: 100%|██████████| 20/20 [00:50<00:00,  2.51s/it]\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\threadpoolctl.py:1226: RuntimeWarning: \n",
      "Found Intel OpenMP ('libiomp') and LLVM OpenMP ('libomp') loaded at\n",
      "the same time. Both libraries are known to be incompatible and this\n",
      "can cause random crashes or deadlocks on Linux when loaded in the\n",
      "same Python program.\n",
      "Using threadpoolctl may cause crashes or deadlocks. For more\n",
      "information and possible workarounds, please see\n",
      "    https://github.com/joblib/threadpoolctl/blob/master/multiple_openmp.md\n",
      "\n",
      "  warnings.warn(msg, RuntimeWarning)\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py64-clustering-series-temporales-forecasting.ipynb (Time: 545.86 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[48/58] Executing: \u001b[93mpy64-clustering-time-series-forecasting.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "Feature Extraction:  95%|█████████▌| 19/20 [00:52<00:01,  1.93s/it]\n",
      "Feature Extraction: 100%|██████████| 20/20 [00:52<00:00,  1.43s/it]\n",
      "Feature Extraction: 100%|██████████| 20/20 [00:52<00:00,  2.63s/it]\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\threadpoolctl.py:1226: RuntimeWarning: \n",
      "Found Intel OpenMP ('libiomp') and LLVM OpenMP ('libomp') loaded at\n",
      "the same time. Both libraries are known to be incompatible and this\n",
      "can cause random crashes or deadlocks on Linux when loaded in the\n",
      "same Python program.\n",
      "Using threadpoolctl may cause crashes or deadlocks. For more\n",
      "information and possible workarounds, please see\n",
      "    https://github.com/joblib/threadpoolctl/blob/master/multiple_openmp.md\n",
      "\n",
      "  warnings.warn(msg, RuntimeWarning)\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1419: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=5.\n",
      "  warnings.warn(\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py64-clustering-time-series-forecasting.ipynb (Time: 567.05 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[49/58] Executing: \u001b[93mpy66-forecasting-sticker-sales-kaggle-es.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py66-forecasting-sticker-sales-kaggle-es.ipynb (Time: 88.53 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[50/58] Executing: \u001b[93mpy66-forecasting-sticker-sales-kaggle.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py66-forecasting-sticker-sales-kaggle.ipynb (Time: 87.55 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[51/58] Executing: \u001b[93mpy69-forecasting-series-temporales-con-catboost.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py69-forecasting-series-temporales-con-catboost.ipynb (Time: 173.74 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[52/58] Executing: \u001b[93mpy69-forecasting-time-series-with-catboost.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\utils\\_tags.py:338: DeprecationWarning:\n",
      "\n",
      "The following error was raised: 'CatBoostRegressor' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order. The default are now used instead since retrieving tags failed. This warning will be replaced by an error in 1.8.\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py69-forecasting-time-series-with-catboost.ipynb (Time: 171.56 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[53/58] Executing: \u001b[93mpy70-drift-detection-forecasting-model.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py70-drift-detection-forecasting-model.ipynb (Time: 14.38 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[54/58] Executing: \u001b[93mpy71-visualizing-time-series-data.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py71-visualizing-time-series-data.ipynb (Time: 12.91 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[55/58] Executing: \u001b[93mpy72-classification-forecasting-categorical-series.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1731: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", result.shape[0])\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1731: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", result.shape[0])\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1731: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", result.shape[0])\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\skforecast\\recursive\\_forecaster_recursive_classifier.py:1922: UserWarning: Impossible to access feature importances for estimator of type <class 'sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier'>. This method is only valid when the estimator stores internally the feature importances in the attribute `feature_importances_` or `coef_`.\n",
      "  warnings.warn(\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py72-classification-forecasting-categorical-series.ipynb (Time: 76.53 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[56/58] Executing: \u001b[93mpy73-arar-forecasting-models-python.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py73-arar-forecasting-models-python.ipynb (Time: 5.98 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[57/58] Executing: \u001b[93mpy74-continuous-ranked-probability-score-CRPS-probabilistic-forecasting.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING (pytensor.configdefaults): g++ not available, if using conda: `conda install gxx`\n",
      "\n",
      "WARNING (pytensor.configdefaults): g++ not detected!  PyTensor will be unable to compile C-implementations and will default to Python. Performance may be severely degraded. To remove this warning, set PyTensor flags cxx to an empty string.\n",
      "\n",
      "C:\\Users\\Joaquin\\miniconda3\\envs\\skforecast_19_py13\\Lib\\site-packages\\pymc_extras\\model\\marginal\\graph_analysis.py:10: FutureWarning: `pytensor.graph.basic.io_toposort` was moved to `pytensor.graph.traversal.io_toposort`. Calling it from the old location will fail in a future release.\n",
      "  from pytensor.graph.basic import io_toposort\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m✓ Success:\u001b[0m py74-continuous-ranked-probability-score-CRPS-probabilistic-forecasting.ipynb (Time: 7.24 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "[58/58] Executing: \u001b[93mpy75-accelerate-forecasting-with-scikit-learn-intelex.ipynb\u001b[0m\n",
      "============================================================\u001b[0m\n",
      "\u001b[92m✓ Success:\u001b[0m py75-accelerate-forecasting-with-scikit-learn-intelex.ipynb (Time: 49.13 seconds)\n",
      "\n",
      "\u001b[96m============================================================\n",
      "EXECUTION SUMMARY\n",
      "============================================================\u001b[0m\n",
      "Total notebooks: \u001b[93m58\u001b[0m\n",
      "Excluded: \u001b[93m7\u001b[0m\n",
      "Successful: \u001b[92m58\u001b[0m\n",
      "Failed: \u001b[91m0\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "# Execute and save all the notebooks in the current directory\n",
    "# ======================================================================================\n",
    "import papermill as pm\n",
    "import os\n",
    "from pathlib import Path\n",
    "import time\n",
    "\n",
    "CONDA_ENV = \"skforecast_19_py13\"\n",
    "NOTEBOOK_DIR = Path(\".\")\n",
    "\n",
    "# Notebooks to exclude (by name or relative path)\n",
    "EXCLUDE_NOTEBOOKS = [\n",
    "    \"00_execute_all_notebooks.ipynb\",\n",
    "    \"00_check_urls.ipynb\",\n",
    "    \"py54-forecasting-con-deep-learning.ipynb\",\n",
    "    \"py54-forecasting-with-deep-learning.ipynb\",\n",
    "    \"py61-m5-forecasting-competition.ipynb\",\n",
    "    \"py65-accelerate-forecasting-models-gpu.ipynb\",\n",
    "    \"py65-acelerar-modelos-forecasting-gpu.ipynb\",\n",
    "]\n",
    "\n",
    "# ANSI color codes\n",
    "class C:\n",
    "    HEADER = \"\\033[96m\"\n",
    "    OK = \"\\033[92m\"\n",
    "    FAIL = \"\\033[91m\"\n",
    "    INFO = \"\\033[93m\"\n",
    "    END = \"\\033[0m\"\n",
    "\n",
    "def run_notebooks():\n",
    "\n",
    "    exclude_set = {str(Path(x)) for x in EXCLUDE_NOTEBOOKS}\n",
    "\n",
    "    notebooks = sorted([\n",
    "        nb for nb in NOTEBOOK_DIR.rglob(\"*.ipynb\")\n",
    "        if \".ipynb_checkpoints\" not in str(nb)\n",
    "        and (nb.name not in exclude_set)\n",
    "        and (str(nb.relative_to(NOTEBOOK_DIR)) not in exclude_set)\n",
    "    ])\n",
    "\n",
    "    results = {\"success\": [], \"failed\": []}\n",
    "\n",
    "    # Show excluded notebooks\n",
    "    if EXCLUDE_NOTEBOOKS:\n",
    "        print(f\"{C.INFO}Excluded notebooks:{C.END}\")\n",
    "        for exc in EXCLUDE_NOTEBOOKS:\n",
    "            print(f\"  - {exc}\")\n",
    "        print()\n",
    "\n",
    "    # Execution loop\n",
    "    for i, notebook in enumerate(notebooks, 1):\n",
    "\n",
    "        print(f\"\\n{C.HEADER}{'='*60}\")\n",
    "        print(f\"[{i}/{len(notebooks)}] Executing: {C.INFO}{notebook.name}{C.END}\")\n",
    "        print(f\"{'='*60}{C.END}\")\n",
    "\n",
    "        # 1. Define a temporary output path\n",
    "        # We append a suffix so we don't touch the original yet\n",
    "        temp_output_path = notebook.with_name(f\"{notebook.stem}_temp_exec{notebook.suffix}\")\n",
    "\n",
    "        try:\n",
    "            start = time.time()\n",
    "            \n",
    "            # 2. Execute into the TEMPORARY path\n",
    "            pm.execute_notebook(\n",
    "                input_path=str(notebook),\n",
    "                output_path=temp_output_path,  # Write to temp file\n",
    "                kernel_name='python3',\n",
    "                progress_bar=False,\n",
    "                log_output=True\n",
    "            )\n",
    "            \n",
    "            end = time.time()\n",
    "            elapsed = end - start\n",
    "            \n",
    "            # 3. If we reach this line, execution was successful.\n",
    "            # Now we atomically replace the original with the executed temp file.\n",
    "            os.replace(temp_output_path, str(notebook))\n",
    "            \n",
    "            results[\"success\"].append(notebook)\n",
    "            print(f\"{C.OK}✓ Success:{C.END} {notebook.name} (Time: {elapsed:.2f} seconds)\")\n",
    "\n",
    "        except Exception as e:\n",
    "            # 4. If execution failed, we clean up the temp file\n",
    "            if os.path.exists(temp_output_path):\n",
    "                os.remove(temp_output_path)\n",
    "                \n",
    "            results[\"failed\"].append((notebook, str(e)))\n",
    "            print(f\"{C.FAIL}✗ FAILED:{C.END} {notebook.name}\")\n",
    "            print(f\"  {C.FAIL}Error:{C.END} {str(e)[:500]}...\")\n",
    "\n",
    "    # Summary\n",
    "    print(f\"\\n{C.HEADER}{'='*60}\")\n",
    "    print(\"EXECUTION SUMMARY\")\n",
    "    print(f\"{'='*60}{C.END}\")\n",
    "\n",
    "    print(f\"Total notebooks: {C.INFO}{len(notebooks)}{C.END}\")\n",
    "    print(f\"Excluded: {C.INFO}{len(EXCLUDE_NOTEBOOKS)}{C.END}\")\n",
    "    print(f\"Successful: {C.OK}{len(results['success'])}{C.END}\")\n",
    "    print(f\"Failed: {C.FAIL}{len(results['failed'])}{C.END}\")\n",
    "\n",
    "    if results[\"failed\"]:\n",
    "        print(f\"\\n{C.FAIL}Failed notebooks:{C.END}\")\n",
    "        for nb, _ in results[\"failed\"]:\n",
    "            print(f\"  {C.FAIL}✗ {nb.name}{C.END}\")\n",
    "\n",
    "run_notebooks()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f0590f8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove outputs from all Jupyter notebooks in the current folder and its subfolders\n",
    "# ==================================================================================\n",
    "# import nbformat\n",
    "# from nbconvert.preprocessors import ClearOutputPreprocessor\n",
    "# from pathlib import Path\n",
    "\n",
    "# folder = Path(\".\")  # current folder, change if needed\n",
    "\n",
    "# def clear_outputs(notebook_path):\n",
    "#     notebook_path = Path(notebook_path)\n",
    "#     nb = nbformat.read(notebook_path, as_version=nbformat.NO_CONVERT)\n",
    "#     ClearOutputPreprocessor().preprocess(nb, {})\n",
    "#     nbformat.write(nb, notebook_path)\n",
    "\n",
    "# for notebook_file in folder.rglob(\"*.ipynb\"):\n",
    "#     clear_outputs(notebook_file)\n",
    "#     print(f\"Cleared outputs: {notebook_file}\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "skforecast_19_py13",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.9"
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 "nbformat": 4,
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